• 보존과학회지
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• 제37권6호
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• pp.801-806
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• 2021

전통 접착 소재인 아교의 사용성과 해초 추출물 카라기난의 겔화 현상을 개선하기 위해 두 재료를 혼합하여 목재 보존용 액상형 접착제를 제조하였으며, 9종의 천연 및 합성 접착제와의 물성 비교를 통해 적용 가능성을 확인하였다. 제조한 목재 접착제는 15 wt% 아교 수용액과 λ-carrageenan, 항균제, 소포제 등을 혼합하였으며, 1.80 Mpa의 최대 접착 강도를 확인하였다. 비교 결과 5종의 전통 천연 접착 성분(수용액)과 Polyvinyl acetate 기반 접착제 1종보다 우수한 접착 강도가 나타났으며, 총호기성생성균수와 유해성(TVOC, HCHO, 중금속) 시험 결과 불검출로 항균성과 안정성을 확인하였다.

• Natural Product Sciences
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• 제28권3호
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• pp.138-142
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• 2022

Alzheimer's disease (AD) is the most common age-related neurodegenerative disease in industrialized countries. It is estimated that about 47 million people living with dementia and the number of cases will be tripled by 2050. However, the exact mechanism of AD is not known, and full therapy has still not been found. Various tryptophan-derived alkaloids have been reported as promising agents for the treatment of AD. In the present study, a series of tryptophan-derived alkaloids were isolated and characterized from the methanol extract of Hedera rhombea fruit. Based on the analysis of their observed and reported spectroscopic data, their structures were identified as N-[4'-hydroxy-(E)-cinnamoyl]-L-tryptophan (1), N-[3',4'-dihydroxy-(E)-cinnamoyl]-L-tryptophan (2), N-[4'-hydroxy-(E)-cinnamoyl]-L-tryptophan methyl ester (3), and N-[3',4'-dihydroxy-(E)-cinnamoyl]-L-tryptophan methyl ester (4). These compounds were screened for anti-Alzheimer activity via their inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes in vitro. As a result, compounds 3 and 4 showed moderate BChE inhibition with IC₅₀ values of 86.9 and 78.4 μM, respectively, compared to those of the positive control [berberine (IC₅₀ = 11.5 μM)]. However, all four compounds did not show significant inhibition of the AChE enzyme. This is the first time, the AChE and BChE inhibitory activities of these tryptophan-derived alkaloids were investigated and reported.

• Natural Product Sciences
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• 제28권4호
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• pp.187-193
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• 2022

Lysimachia christinae Hance was commonly used in Oriental medicine for treating the hepatitis virus, cholecystitis and cholagogic efficiency. According to the previous study, it possesses high antioxidant and anti-inflammatory activity. Simultaneous determination analytical method of isolated eight compounds, cynaroside (1), 2-(3,4-dimethoxyphenyl) ethyl O-α-L-arabinopyranosyl-(1→2)-O-[6-deoxy-α-L-mannopyranosyl-(1→3)] β-D-glucopyranoside (2), stearylester ricinoleic acid (3), (E)-4-(3,4-dimethoxyphenyl) but-3-en-1-yl palmitate (4), 2-hydroxy-24-methoxy-4-tetracosenoic acid (5), 2-hydroxy-24-propoxy-4-tetracosenoic acid (6), β-sitosterol (7), and androst-16-ene-3,6-diol (8) were established by using HPLC-DAD. This HPLC analysis was detected on a Dionex C18 column (5 ㎛, 120 Å, 4.6 mm × 150 mm) at 25℃. The mobile phase consisted of 0.1% trifluoroacetic acid and acetonitrile at a flow rate of 1 mL/min. Validation of the method was assessed by linearity, precision and accuracy test. Calibration curve was good at r² > 0.9998. Limits of detection (LOD) ranged from 0.19 to 8.18 g/ml and Limits of quantification (LOQ) ranged from 0.19 to 24.80 g/ml. The relative standard deviations (RSD) values of precision test, intra- and inter- day, were less than 0.99% and 1.0%. The accuracy test results ranged from 98.81% to 106.49% and RSD values were less than 0.95%. These results showed that the HPLC-DAD method was very reliable and accurate for the quantity analysis of eight compounds in L. christinae extract for quality control.

• 한국컴퓨터정보학회논문지
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• 제28권9호
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• pp.35-46
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• 2023

본 연구에서는 문서 분류기의 정확도를 높이기 위해 문맥 정보와 키워드 정보를 모두 사용하는 이중 접근(Dual Approach) 방법론을 제안한다. 우선 문맥 정보는 다양한 자연어 이해 작업(Task)에서 뛰어난 성능을 나타내고 있는 사전학습언어모델인 Google의 BERT를 사용하여 추출한다. 구체적으로 한국어 말뭉치를 사전학습한 KoBERT를 사용하여 문맥 정보를 CLS 토큰 형태로 추출한다. 다음으로 키워드 정보는 문서별 키워드 집합을 Autoencoder의 잠재 벡터를 통해 하나의 벡터 값으로 생성하여 사용한다. 제안 방법을 국가과학기술정보서비스(NTIS)의 국가 R&D 과제 문서 중 보건 의료에 해당하는 40,130건의 문서에 적용하여 실험을 수행한 결과, 제안 방법이 문서 정보 또는 단어 정보만을 활용하여 문서 분류를 진행하는 기존 방법들에 비해 정확도 측면에서 우수한 성능을 나타냄을 확인하였다.

• 한국엔터테인먼트산업학회논문지
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• 제13권4호
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• pp.63-70
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• 2019

상황 인식 환경에서 공황장애의 증상을 추출하고자 일상생활을 통해 자연스런 음직임에서 발생하는 신체 상황정보를 추출하여 공황장애의 구성요소를 찾아내고 온톨로지 이론을 적용하여 의미를 추론 과정을 거쳐 공황장애에 증상의 정도에 대해 정보를 제공할 수 있다. 온톨로지 기반의 정보 처리를 위해 공황장애의 구성요소는 클래스로 정의하고 공황장애의 상태를 이해할 수 있도록 온톨로지 모델링을 통해 공황장애지수를 도출하였다. 공황장애 구성요소와 공황장애 지수의 도출은 공황장애에 대한 상황 인식 기반의 정보 서비스를 가능할 것이며, 상황인식 기반 디바이스와 결합되어 상황정보는 주기적으로 동기화된다. 공황장애 지수의 결과를 관찰할 수 있으며 공황장애의 요인이 되는 생활습관을 개선하는데 적용할 수 있을 것이다.

• 한국엔터테인먼트산업학회논문지
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• 제13권1호
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• pp.217-223
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• 2019

본 연구는 사람의 대장암에 천연물인 과라나와 그라비올라가 어떤 효능을 나타내는지를 확인하고자 항산화 활성과 항암활성을 분석하였다. 각각 에탄올로 추출하여 control, 25.0, 50.0, 75, 100.0mg/ml의 농도에서 DPPH분석한 결과 과라나는 50mg/ml에서 80.9%, 그라비올라는 71.4%의 소거율을 보여 유의적인 항산화 활성이 있음을 확인하였다. 인체 대장암 세포주인 HCT-116에서 MTT assay와 FACS에 의한 apoptotic rate로 항암효과를 조사한 결과, 과라나와 그라비올라 모두 세포증식을 강하게 억제하였으며, 특히 10mg/ml의 농도에서 과라나는 96.65±3.71, 그라비올라는 76.58±2.87%의 높은 apoptotic rate를 나타냄으로써 뚜렷한 항암 효과가 있음을 확인하였다. 이와 같은 결과는 천연 식물성 성분인 과라나와 그라비올라가 대장암의 예방과 치료에 새로운 항암제로서의 기초자료를 제공하는 것이며, 향후 국민건강 및 의료비 절감에도 기여할 수 있을 것으로 기대된다.

• 한국환경농학회지
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• 제41권1호
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• pp.50-54
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• 2022

BACKGROUND: Phyllospadix japonica Makino is a perennial plant belonging to the family Zosteraceae. This species is native to the eastern coast of the Korean Peninsula, and it is found attached to rocks on the seashore. As with all seagrass species, P. japonica is also known to play a major role in protecting the marine environment, and studies on its physiological activities suggestive of its antioxidant, antibacterial and anti-inflammatory potentials have been reported. In this study, purification and structural analysis were performed to identify the polyphenol substances derived from P. japonica. METHODS AND RESULTS: An polyphenol substance MP-1 was purified from the 70% aqueous methanol extract of P. japonica using Diaion® HP-20 column chromatography, ODS column chromatography, and medium-pressure liquid chromatography (MPLC). The purified MP-1 was identified as rosmarinic acid having a molecular weight of 360 and a molecular formula of C18H16O8 through electrospray ionization (ESI)-mass and nuclear magnetic resonance (NMR) spectroscopic analysis. CONCLUSION(S): This study highlights the processes used for the identification of the polyphenol substance derived from P. japonica. Rosmarinic acid, the polyphenol derived from P. japonica identified by this study, is a kind of bioactive substance mainly present in plants. These findings provide an important starting point and are valuable for future studies on bioactive substances in seagrass.

• Journal of Ginseng Research
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• 제47권4호
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• pp.593-603
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• 2023

Background: Korean Red Ginseng is a major source of bioactive substances such as ginsenosides. Efficacy of red ginseng extract (RGE), which contains not only saponins but also various non-saponins, has long been studied. In the water-soluble component-rich fraction of RGE (WS), a byproduct generated in the process of extracting saponins from the RGE, we identified previously unidentified molecules and confirmed their efficacy. Methods: The RGE was prepared and used to produce WS, whose components were isolated sequentially according to their water affinity. The new compounds from WS were fractionized and structurally analyzed using nuclear magnetic resonance spectroscopy. Physiological applicability was evaluated by verifying the antioxidant and anti-inflammatory efficacies of these compounds in vitro. Results: High-performance liquid chromatography confirmed that the obtained WS comprised 11 phenolic acid and flavonoid substances. Among four major compounds from fractions 1-4 (F1-4) of WS, two compounds from F3 and F4 were newly identified in red ginseng. The analysis results show that these compound molecules are member of the maltol-structure-based glucopyranose series, and F1 and F4 are particularly effective for decreasing oxidative stress levels and inhibiting nitric oxide secretion, interleukin (IL)-1β and IL-6, and tumor necrosis factor-α. Conclusion: Our findings suggest that a few newly identified maltol derivatives, such as red ginseng-derived non-saponin in the WS, exhibit antioxidant and anti-inflammatory effects, making them viable candidates for application to pharmaceutical, cosmetic, and functional food materials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• 대한토목학회논문집
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• 제28권2A호
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• pp.215-222
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• 2008

본 논문은 현수교 이중 행어 시스템에 대한 진동기반 SI 장력추정기법의 실험적 검증을 소개한다. 현수교 이중 행어 시스템을 모사한 실험 모델을 제작되었으며, 세가지 경우의 클램프 위치에 대한 세가지 경우의 행어장력에 대해서 총 9회의 진동실험이 반복 수행되었다. 각각의 계측된 가속도 응답 데이터에 대해서, 모달분석을 통한 고유진동수와 모드 형상이 추출되었다. 추출된 일련의 동특성치들에 대하여 기존의 장력추정 이론인 현이론과 선형회기법을 적용하여 장력을 추정하였다. 또한 진동기반 SI 장력추정기법을 적용하여 장력을 추정하였는데, 추정된 장력은 수치모델과 계측모델의 동적 특성치들이 동일하게 될 때, 수치모델의 케이블 장력을 인식함으로써 추정되었다. 추정결과, 클램프의 위치에 따라서 기존의 이론을 이용한 추정장력의 오차는 최대 53.1%까지 보이는 반면, 진동기반 SI기법을 이용한 추정장력기법의 장력추정 오차는 모든 경우에 대하여 3% 이내 이다.